Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Sustainable Decision Making (Prof. Dr. Clemens Thielen), which is located at the TUM Campus Straubing for Biotechnology and Sustainability (TUMCS) and affiliated with the Department of Mathematics. The expected
-
The Data Integration in the Life Sciences group, led by Prof. Dr. Katharina Baum, is seeking a motivated student assistant to contribute to the cutting-edge, BMBF-funded research project Act-i-ML
-
Dr. Darius Bunandar, the Boston University team is led by Prof. Ajay Joshi, and the Harvard University team is led by Prof. Vijay Janapa Reddi. Role Our team has two postdoctoral researcher openings
-
Postdoctoral Research Scientist with Prof. Raimondo Betti, Department of Civil Engineering & Engineering Mechanics and Principal Investigator, and Prof. Homayoon Beigi, Department of Mechanical/Electrical
-
processing, inverse problems and data science with emphasis on analysis, optimization, numerics and algorithmic solution Collaboration in interdisciplinary cooperation projects and third-party funded projects
-
Australian National University | Canberra, Australian Capital Territory | Australia | about 9 hours ago
to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited to Bayesian machine learning, human-centered AI and interpretable machine learning, attention markets, gig
-
learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
-
comprises four faculty (Profs. Chang, Konigsberg, Korytov, and Takahashi), five postdocs, five graduate students, and a group of engineers and technical personnel — making us one of the largest U.S
-
developed by the project partners will be based on two key technologies: machine learning algorithms that generate artificial yet realistic data points (synthetic health data) and secure multi-party
-
of algorithms and digital neuromorphic hardware is an additional avenue for enhancing the efficiency of the methods. In this context the research will explore digital, event-based implementations